Abnormal eye movement features in patients with depression: Preliminary findings based on eye tracking technology

Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method...

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Published inGeneral hospital psychiatry Vol. 84; pp. 25 - 30
Main Authors Gao, Mingzhou, Xin, Rongrong, Wang, Qingxiang, Gao, Dongmei, Wang, Jieqiong, Yu, Yanhong
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.09.2023
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Abstract Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression. Thirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups. In the prosaccade task, there was no difference between the depression and control groups(t = 0.019, P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72, P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253, P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task. Patients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.
AbstractList Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression.BACKGROUNDSaccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression.Thirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups.METHODSThirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups.In the prosaccade task, there was no difference between the depression and control groups(t = 0.019, P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72, P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253, P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task.RESULTSIn the prosaccade task, there was no difference between the depression and control groups(t = 0.019, P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72, P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253, P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task.Patients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.CONCLUSIONPatients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.
Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression. Thirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups. In the prosaccade task, there was no difference between the depression and control groups(t = 0.019, P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72, P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253, P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task. Patients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.
Author Gao, Dongmei
Wang, Jieqiong
Wang, Qingxiang
Gao, Mingzhou
Yu, Yanhong
Xin, Rongrong
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Keywords Biomarkers
Depression
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Eye-tracking
Eye movement deficits
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Snippet Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not...
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SubjectTerms Auxiliary diagnosis
Biomarkers
Depression
Eye movement deficits
Eye-tracking
Title Abnormal eye movement features in patients with depression: Preliminary findings based on eye tracking technology
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0163834323000683
https://dx.doi.org/10.1016/j.genhosppsych.2023.04.010
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